Abstract: Dynamic stream learning, which emphasizes high-velocity, single-pass, real-time responses to arriving data, is revealing new challenges to the standard machine learning paradigm. In ...

These efforts are promising but limited. AI minds don't necessarily map to human concepts. Some believe that we need to ...

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

Abstract: Due to their synaptic-like characteristics and memory properties, memristors are often used in neuromorphic circuits, particularly neural network circuits. However, most of the existing ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

This repository contains a time series forecasting project using the Google Play Store dataset. It systematically compares RNN, LSTM, and GRU models, optimized via Keras Tuner, to predict future app ...

College of Integrated Circuits and Micro-Nano Electronics, School of Microelectronics, State Key Laboratory of Integrated Chip and System, Fudan University, Shanghai 200433, China ...

Introduction: Segmentation of echocardiograms plays a crucial role in clinical diagnosis. Beyond accuracy, a major challenge of video echocardiogram analysis is the temporal consistency of consecutive ...