What are some recent advancements in CNN architectures?

Abstract. We present Point-Voxel CNN (PVCNN) for efficient, fast 3D deep learning. Previous work processes 3D data using either voxel-based or point-based NN ... Nov 14, 2023 ... A Convolutional Neural Network (CNN), also known as ConvNet, is a specialized type of deep learning algorithm mainly designed for tasks that necessitate object ... We have proposed a deep learning method called BCM-SegNet, an optimized Mask R-CNN-based algorithm for segmenting BSE images of bronze casting moulds and cores. Mar 25, 2025 ... We introduce CNN-TumorNet, an innovative method for brain tumor classification utilizing a deep convolutional neural network (CNN) for the ... Feb 10, 2020 ... The main novelty of this study was to build a coupled CNN–LSTM model to predict water quality variables. Two traditional machine learning models ... Apr 3, 2023 ... A CNN works by transforming an input image into a feature map, which is then processed through multiple convolutional and pooling layers to ... With the increase in computational parallelism and low-power Integrated Circuits (ICs) design, neuromorphic technologies and machine learning algorithms ... Explore and run machine learning code with Kaggle Notebooks | Using data from Digit Recognizer. Jan 23, 2023 ... Comparing the performance of various CNNs and machine learning methods in diagnosing three types of brain tumors revealed that the 2D CNN ... A convolutional neural network (CNN) is a type of artificial neural network used primarily for image recognition and processing.