What if the future of robotics wasn’t a single machine but an intelligent swarm, moving as one, adapting to its environment, and executing tasks with precision? Imagine a fleet of drones navigating a ...
In recent years, the exploitation of three-dimensional (3D) data in deep learning has gained momentum despite its inherent challenges. The necessity of 3D approaches arises from the limitations of two ...
'Space object' crashes into remote Kenyan village Link Copied! A huge, red-hot object fell from the sky into a Kenyan village, according to local residents cited by the country’s national broadcaster, ...
Abstract: This study focuses on enhancing the accuracy and efficiency of semantic analysis systems for recognizing moving objects within video sequences. The primary aim is to improve object detection ...
In order to more accurately detect the accuracy of word-wheel water meter digits, 2000 water meter pictures were produced, and an improved Faster-RCNN algorithm for detecting water meter digits was ...
Objective: Explore a new deep learning (DL) object detection algorithm for clinical auxiliary diagnosis of lumbar spondylolisthesis and compare it with doctors’ evaluation to verify the effectiveness ...
This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature ...
Abstract: The aim of this work is to implement a Convolutional Neural Network (CNN) using a Python framework on Xilinx® Zynq® based Field Programmable Gate Array (FPGA). And the prototype is used to ...
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