convolutional neural network
PulseAugur coverage of convolutional neural network — every cluster mentioning convolutional neural network across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
Deep learning receiver boosts asynchronous comms in control networks
Researchers have developed a novel deep learning-based receiver designed to improve asynchronous grant-free random access in control-to-control communication networks. This system utilizes a convolutional neural network…
-
Foundation model learns from Dutch satellite data for global benchmarks
Researchers have developed a new foundation model for high-resolution remote sensing data, specifically trained on satellite images of the Netherlands. This model combines Convolutional Neural Networks and Vision Transf…
-
Deep learning model predicts full-chip CMP nanotopography with nanometer accuracy
Researchers have developed a novel deep learning model to predict the full-chip post-Chemical-Mechanical Polishing (CMP) nanotopography with nanometer-scale accuracy. This model combines data from White Light Interferom…
-
CNN achieves 91.79% accuracy for Hindi keyword spotting in speech recognition
Researchers have developed a keyword spotting system for Hindi speech recognition using a Convolutional Neural Network (CNN). The system was trained on 40,000 audio samples and utilizes Mel Frequency Cepstral Coefficien…
-
New BerLU activation function improves deep learning stability and efficiency
Researchers have introduced a new activation function called the Bernstein Linear Unit (BerLU) that aims to improve the stability and efficiency of deep neural networks. By utilizing Bernstein polynomials, BerLU creates…
-
New SISA framework enables efficient class-level machine unlearning in CNNs
Researchers have developed a novel machine unlearning technique specifically for removing entire classes of data from deep neural networks. This method modifies the Sharded, Isolated, Sliced, and Aggregated (SISA) frame…
-
New OCR pipeline enhances retail bill digitization with adaptive enhancement
Researchers have developed and benchmarked an adaptive Optical Character Recognition (OCR) pipeline specifically designed for digitizing diverse retail bills. This system incorporates a CNN-based enhancement module, an …
-
AI identifies writers of historical Arabic manuscripts with high accuracy
Researchers have developed a Convolutional Neural Network (CNN) with attention mechanisms to identify writers of historical Arabic manuscripts. The study, using the Muharaf dataset, expanded writer labels and establishe…
-
CNNs and personalized thresholds improve driver drowsiness detection accuracy
Researchers have developed a new driver drowsiness detection system that uses personalized thresholds for Eye Aspect Ratio (EAR) and Mouth Aspect Ratio (MAR) to account for individual differences. The system integrates …