16 skills found
doans / Underwater Acoustic Target Classification Based On Dense Convolutional Neural NetworkIn oceanic remote sensing operations, underwater acoustic target recognition is always a difficult and extremely important task of sonar systems, especially in the condition of complex sound wave propagation characteristics. Expensively learning recognition model for big data analysis is typically an obstacle for most traditional machine learning (ML) algorithms, whereas convolutional neural network (CNN), a type of deep neural network, can automatically extract features for accurate classification. In this study, we propose an approach using a dense CNN model for underwater target recognition. The network architecture is designed to cleverly re-use all former feature maps to optimize classification rate under various impaired conditions while satisfying low computational cost. In addition, instead of using time-frequency spectrogram images, the proposed scheme allows directly utilizing original audio signal in time domain as the network input data. Based on the experimental results evaluated on the real-world dataset of passive sonar, our classification model achieves the overall accuracy of 98.85$\%$ at 0 dB signal-to-noise ratio (SNR) and outperforms traditional ML techniques, as well as other state-of-the-art CNN models.
idanstei / Superiorized Photo Acoustic Non NEgative Reconstruction For Clinical Photoacoustic ImagingPhotoacoustic (PA) imaging can revolutionize medical ultrasound by augmenting it with molecular information. However, clinical translation of PA imaging remains a challenge due to the limited viewing angles and imaging depth. Described here is a new robust algorithm called Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER), designed to reconstruct PA images in real-time and to address these limitations. The method utilizes precise forward modeling of the PA propagation and reception of signals while accounting for the effects of acoustic absorption, element size, shape, and sensitivity, as well as the transducer's impulse response and directivity pattern. A fast superiorized conjugate gradient algorithm is used for inversion. SPANNER is compared to three reconstruction algorithms: delay-and-sum (DAS), universal back-projection (UBP), and model-based reconstruction (MBR). All four algorithms are applied to both simulations and experimental data acquired from tissue-mimicking phantoms, ex vivo tissue samples, and in vivo imaging of the prostates in patients. Simulations and phantom experiments highlight the ability of SPANNER to improve contrast to background ratio by up to 20 dB compared to all other algorithms, as well as a 3-fold increase in axial resolution compared to DAS and UBP. Applying SPANNER on contrast-enhanced PA images acquired from prostate cancer patients yielded a statistically significant difference before and after contrast agent administration, while the other three image reconstruction methods did not, thus highlighting SPANNER's performance in differentiating intrinsic from extrinsic PA signals and its ability to quantify PA signals from the contrast agent more accurately.
Miner-Zhang / Deep Learning Models In Modulation ClassificationThis project utilizes three deep learning models, DNN, CNN, and LSTM, for the classification and recognition of 11 modulation types, including BPSK, QPSK, 8PSK, 16QAM, 64QAM, PAM4, GFSK, CPFSK, B-FM, DSB-AM, and SSB-AM, under varying signal-to-noise ratio conditions.
aloelabs / Aloe BlendMaximizing liquidity utilization while maintaining 50/50 inventory ratio
truefrontier / Tailwindcss Golden RatioA Tailwind CSS plugin to utilize the Golden Ratio in spacing, height, width, scale, borderWidth, and lineHeight
BUILTNYU / EVQUARIUMEVQUARIUM is an evaluation tool that quantifies the accessibility of EV charging station locations using queueing and graph theory. Given a zonal distribution of EVs with access times to charging stations, it outputs the access patterns and social impacts under equilibrium.
JNDreviews / Est Smartphones Under Rs.15000 WHICH ARE THE BEST SMARTPHONES UNDER 15000 . Best Smartphones under Rs.15000 models 2021 Step by step instructions to track down the best cell phones under Rs.15,000?Take a look Cell phones have turned into a central piece of our life. We can't ponder our existence without cell phones. Assuming you are hoping to purchase a Smartphones under ₹15,000, look at our rundown. There are various cell phones accessible in the various sections yet Smartphones under Rs.15,000 are the most jammed cell phone fragment in the Indian market. We get cell phones that offer fantastic worth and progressed components and execution. The accompanying elements that ought to be thought of while purchasing a Smartphone under Rs.15,000 are battery execution, quick charging, great showcase, nice execution and gaming experience, RAM, Processor, camera, working framework, and all that things are remembered for the underneath cell phones list. Cell phones makers center around making quality innovation that is available for everybody. On the off chance that you are searching for a cell phone in your spending plan, look at the beneath rundown of Best Smartphones under Rs.15,000. Here is the current rundown of Best Smartphones under Rs 15,000: Redmi Note 10 Realme 8 Realme Narzo 30 Samsung Galaxy M32 Motorola Moto G30 Redmi Note 10: WHICH ARE THE BEST SMARTPHONES UNDER 15000 Best Smartphones under Rs.15000 models 2021 Redmi Note 10 is one of the Most outstanding Smartphone under Rs.15000.Redmi has as of late refreshed its Note Series. This gadget accompanies a splendid 6.43 inch full HD show and offers great execution. As far as battery life, this cell phone is the best 5,000mAh battery which can undoubtedly most recent daily, charges from 0 to half inside 30 minutes. It has a super AMOLED show that permits you to encounter a smooth and vivid survey insight. Redmi Note 10 controlled by the Qualcomm Snapdragon 678 SoC processor that is amazing enough for relaxed gaming just as ordinary undertakings. Photography is streamlined with a 48 MP Quad Rear camera with a 8MP Ultra-wide focal point, 2MP Macro, and Portrait focal point on the front 13 MP selfie camera. It can record 4K@30fps, support magnificence mode, slow movement, and different elements. Redmi Note 10 has double sound system speakers with Hi-Res ensured sound for a vivid sound encounter. The side-mounted unique finger impression sensor accompanies a flush plan to give you an exceptional vibe. Presently you can open your gadget effectively with a smidgen. Shields your gadget from unforeseen falls and undesirable scratches with Corning Gorilla glasses. Redmi Note 10 comes in 3 distinctive slick shadings Aqua Green, Shadow Black, Frost white.3.5mm sound jack, simply attachment and play for constant amusement. Specialized Specification: Measurements (mm):160.46 x 74.50 x 8.30 Weight (g):178.80 Battery limit (mAh):5000 Quick charging: Proprietary Tones: Aqua Green, Frost White, Shadow Black Show: Screen size (inches):6.43 Touchscreen:Yes Resolution:1080×2400 pixels Assurance type:Gorilla Glass Processor octa-center Processor make Qualcomm Snapdragon 678 RAM:4GB Interior storage:64GB Expandable storage:Yes Expandable capacity type:microSD Expandable capacity up to (GB):512 Committed microSD space: Yes Back camera:48-megapixel + 8-megapixel + 2-megapixel)+ 2-megapixel No. of Rear Cameras:4 Back autofocus:Yes Back Flash: Yes Front camera:13-megapixel No. of Front Cameras:1 Working framework: Android 11 Skin: MIUI 12 Finger impression sensor: Yes Compass/Magnetometer:Yes Nearness sensor: Yes Accelerometer: Yes Surrounding light sensor: Yes Spinner : Yes Experts Eye-getting plan. Great camera yield from the essential camera. Great presentation and incredible battery life. Cons Baffling gaming execution. Realme 8 : The Realme 8 is a decent gadget for media utilization with an alluring striking plan. experience splendid, distinctive shadings with a 6.4″ super AMOLED full showcase. A touch inspecting pace of 180Hz.The fast in-show unique mark scanner gives a simpler open encounter. It accompanies a 5000mAh battery viable with 30W Fast Charging innovation. Hey Res affirmed sound for a vivid sound experience.The super-flimsy 7.99mm and 177g design.6GB RAM with 128GB in-assembled capacity. The Neon Portrait highlights assist with featuring your magnificence. The Dynamic Bokeh highlights assist you with taking more jazzy and dynamic pictures. The front and back cameras assist you with exploiting your inventiveness. Quickly charge the gadget to 100% in only 65 minutes. By utilizing slant shift mode you can add smaller than normal impacts to your photographs to make them look adorable and excellent. Assuming you are searching for Smartphones under Rs.15,000, you can go for Realme 8. We should take a gander at some specialized components: Measurements (mm):160.60 x 73.90 x 7.99 Weight (g):177.00 Battery limit (mAh):5000 Quick charging: Proprietary Shadings: Cyber Black, Cyber Silver Screen size (inches):6.40 Touchscreen: Yes Resolution:1080×2400 pixels Processor octa-center Processor make: MediaTek Helio G95 RAM:8GB Inner storage:128GB Expandable capacity: Yes Expandable capacity type:microSD Back camera:64-megapixel + 8-megapixel + 2-megapixel + 2-megapixel No. of Rear Cameras:4 Back self-adjust: Yes Back Flash: Yes Front camera:16-megapixel No. of Front Cameras:1 Working framework: Android 11 Skin: Realme UI 2.0 Face open: Yes In-Display Fingerprint Sensor: Yes Compass/Magnetometer:Yes Closeness sensor: Yes Accelerometer: Yes Encompassing light sensor: Yes Gyrator : Yes Stars Cons Dependable execution Disillusioning camera experience 90Hz revive rate show Bloatware-perplexed UI Great battery life. Slow charging Realme Narzo 30: On the off chance that you are searching for Best Smartphones under Rs.15,000, look at this Realme Narzo 30. The Realme Narzo 30 is a recently dispatched cell phone with brilliant components. Realme is one of the quickest developing brand in the Indian market. Going to its particulars, the new gadget has a splendid 6.5″ presentation which can assist you with opening up a totally different skyline. The cell phone has a huge 5000mAh battery. The gadget accompanies a MediaTek Helio G-85 octa-center processor. Realme Narzo 30 displays 64GB that is further expandable up to 256GB utilizing a microSD card. It accompanies a 48 MP AI Triple Camera with a 16MP front camera. It offers availability alternatives like Mobile Hotspot, Bluetooth v5.0, A-GPS Glonass, WiFi 802.11, USB Type-C, USB Charging alongside help for 4G VoLTE organization. This presentation of this Realme Narzo 30 offers a smooth looking over experience. This Realme Narzo 30 components a race track-roused V-speed configuration to offer an exciting, restless look. The realme Narzo 30 has Android 11 OS, and it is smooth and easy to use. The Realme Narzo 30 is one of the Most amazing Smartphone under Rs.15,000. We should take a gander at some specialized provisions: Screen Size (In Inches):6.5 Show Technology :IPS LCD Screen Resolution (In Pixels):1080 x 2400 Pixel Density (Ppi):270 Invigorate Rate:90 Hz Camera Features:Triple Back Camera Megapixel:48 + 2 + 2 Front Camera Megapixel:16 Face Detection:Yes Hdr:Yes Battery Capacity (Mah):5000 Quick Charging Wattage:30 W Charging Type Port :Type-C Cpu:Mediatek Helio G95 Central processor Speed:2×2.05 GHz, 6×2.0 GHz Processor Cores:Octa Ram:4 GB Gpu:Mali-G76 MC4 Measurements (Lxbxh-In Mm):162.3 x 75.4 x 9.4 Weight (In Grams):192 Storage:64 GB Stars Extraordinary presentation to watch recordings. Respectable essential camera in daytime. Cons Helpless low-light camera execution. Samsung Galaxy F22: Samsung presents the Samsung universe F22 cell phone which is the Best Smartphone under Rs.15,000.if you are a moderate client like online media, observe a few recordings, and mess around for the sake of entertainment, then, at that point this telephone is intended for you. Keeping in see the mid-range level of passage Samsung has made its quality felt inside the majority. Eminent telephone with a heavenly look and very magnificent execution Samsung Galaxy F22 accompanies a 16.23cm(6.4″)sAMOLED vastness U showcase. Super AMOLED with HD very much designed which is satisfying to the eye for long viewing.Glam up your feed with a genuine 42MP Quad camera. Consistent performing various tasks, monstrous capacity, and force loaded with the MTK G80 processor.Scanner.Available in two cool shadings Denim dark, Denim blue. Samsung Galaxy F22 accompanies a 6000mAh battery so you can go a whole day without having to continually re-energize. Each photograph that you catch on this Samsung cosmic system F22 will be clear and reasonable. make your installment speedy and quick by utilizing Samsung pay smaller than usual. We should take a gander at some specialized components: Measurements (mm):159.90 x 74.00 x 9.30 Weight (g):203.00 Battery limit (mAh):6000 Screen size (inches):6.40 Touchscreen:Yes Resolution:720×1600 pixels Assurance type:Gorilla Glass Processor:octa-center Processor make:MediaTek Helio G80 RAM:4GB Inward storage:64GB Working system:Android 11 Back camera:48-megapixel 8-megapixel + 2-megapixel + 2-megapixel No. of Rear Cameras:4 Back autofocus:Yes front camera:13-megapixel No. of Front Cameras:1 Aces: 90 Hz Refresh Rate. Samsung Pay Mini. Up-to-date Design.Motorola Moto G30: Motorola Moto G30: Motorola has dispatched Moto G30 is one of the Most outstanding Smartphones under Rs.15,000 in India. The cell phone has Android 11 OS with a close stock interface. Moto G30 accompanies a quad-camera which incorporates a 64MP essential sensor and 13 MP camera at the front. Moto G30 has two distinct shadings Dark Pearl and Pastel Sky tones. Moto G30 accompanies a 6.5-inch HD show with a 20:9 angle ratio,90Hz revive rate, and 720*1600 pixels show goal. The Moto G30 runs on Android 11. The telephone is stacked with highlights like Night Vision, shot advancement, Auto grin catch, HDR, and RAW photograph output.it is controlled by a Qualcomm Snapdragon 662 octa-center processor alongside 4 GB of RAM.it accompanies 64 GB of installed stockpiling that is expandable up to 512GB by means of a microSD card. Moto G30 has a 5,000mAh battery that can go more than 2 days on a solitary charge. Far reaching equipment and programming security ensure your own information is better ensured. By utilizing NFC innovation assists you with making smooth, quick, and secure installments when you hold it close to a NFC terminal.Connectivity choice incorporate Wi-Fi 802.11 a/b/g/n/ac, GPS, Bluetooth v5.00, NFC, and USB Type-C.It has measurements 169.60 x 75.90 x 9.80mm and weighs 225.00 g. We should take a gander at some specialized components: Manufacturer:Moto Model:G30 Dispatch Date (Global):09-03-2021 Working System:Android Operating system Version:11 Display:6.50-inch, 720×1600 pixels Processor:Qualcomm Snapdragon 662 RAM:4GB Battery Capacity:5000mAh Back Camera: 64MP + 8MP +2MP Front Camera:13MP Computer chip Speed:4×2.0 GHz, 4×1.8 GHz Processor Cores:Octa-center Gpu:Adreno 610 Measurements (Lxbxh-In Mm) :165.2 x 75.7 x 9.1 Weight (In Grams) :200 Storage:128 GB Quick Charging Wattage:20W Charging Type Port:Type-C Experts: High invigorate rate show Clean Android 11 UI Great battery execution Good cameras Cons: Huge and cumbersome Forceful Night mode. 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edvujic / LZ77 DEFLATE CompressionDEFLATE combines the LZ77 algorithm and Huffman Coding to achieve high compression ratios. This project is designed to be a straightforward and practical resource for anyone looking to understand or utilize DEFLATE compression in their applications.
a4021340213 / Adaptive Beamforming For Directional Signal EnhancementDesigned an adaptive beamforming system utilizing AIC-SVD for DOA denoising and the RAIS-LCMV algorithm for spatial filtering. This system demonstrated superior signal-to-noise ratio (SNR) and enhanced interference suppression compared to the traditional LCMV beamformer, particularly in dynamic environments with varying source and interference dire
liuchb715 / DMSGWNN GURDMSGWNN: Denoising Multiscale Spectral Graph Wavelet Neural Networks for Gas Utilization Ratio Prediction in Blast Furnace (TNNLS, 2024)
Akhil1409906 / Eye Blink DetectionThe Real-Time Eye Blink Detection and Counting project uses OpenCV and dlib to detect and count eye blinks in real-time through a webcam feed. It utilizes dlib's facial landmark detection model to locate key points around the eyes and calculates the blinking ratio.
ccs19 / MGSV TPP WideScreen PatchPatches the MGSV executable to properly utilize ultrawide aspect ratios, Nvidia Surround, and Eyefinity
dlut-dimt / TGDOF# TGDOF This is the testing code of TGDOF for CS-MRI. Running the script "AddPath" and then the "Demo_TGDOF" to test the basic deep framework for CS-MRI. TestData ------------ The testing MR slices used in experiments, including 25 T1-weighted data and 25 T2-weighted data. The slices are extracted from the subset of the IXI datasets: http://brain-development.org/ixi-dataset/ ArtifactsModel ------------ The pre-trained model used in Module \mathcal{N}. SamplingPatter: ------------ The three kinds of sampling patterns at five different sampling ratios (10% to 50%). If you utilize this code, please cite the related paper: <br> @inproceedings{liu2019theoretically,<br> title={A theoretically guaranteed deep optimization framework for robust compressive sensing mri},<br> author={Liu, Risheng and Zhang, Yuxi and Cheng, Shichao and Fan, Xin and Luo, Zhongxuan},<br> booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},<br> volume={33},<br> pages={4368--4375},<br> year={2019} }
KhaledAshrafH / DT Banknote AuthenticatorThis Python code utilizes the decision tree algorithm from the scikit-learn library to perform banknote authentication. The code aims to analyze the impact of different train-test split ratios and training set sizes on the accuracy and size of the learned decision tree.
BSEL-UC3M / EHRatioAnalysisThis repository contains a Python-based automated pipeline utilizing Deep Learning techniques to estimate Endolymphatic Hydrops (EH) ratios from 3D MRI sequences, aiding in the diagnosis of Ménière's Disease.
liwentao-319 / Sequential RFAC Hk StackingSequential RF-AC H-k Stacking utilize the seismic converted phases from Receiver Functions and the seismic reflected phases from coda Autocorrelations of teleseismic P-waves to constrain the thicknesses and Vp/Vs ratios of the sediments and the underlying crust.
