In this paper, an object detection algorithm for UAV reconnaissance image based on deep convolution network is proposed. The image is adaptively divided according to the UAV flight parameters and the payload parameters before sent into the network. Through this way, small objects can be located ...
an object detection algorithm based on deep learning and salient feature fusion is proposed. The proposed method introduces a non-weight-sharing network to process the salient features of the image and fuse them with the features extracted from the red blue green branch. Different from the previous...
Then, an object detection algorithm is combined with a depth camera ranging algorithm, which can inspect the 3D coordinates of the weld groove in real-time with limited computing resources. The algorithm was deployed on a host computer for welding robot guiding experiments, and the results showed...
SNIPER is an efficient multi-scale training approach for instance-level recognition tasks like object detection and instance-level segmentataion. Instead of processing all pixels in an image pyramid, SNIPER selectively processes context regions around the ground-truth objects (a.k.a chips). This ...
The open-source object detection library MMDetection45 was used as the implementation platform for the algorithms. For the parameter settings, the batch size was set to 16, the stochastic gradient descent algorithm was selected to optimize the learning rate, the momentum was set to 0.9, the ...
To solve this issue, we attend to study the object detection algorithm in the scenarios for both daytime as well as dark scene. Considering the high efficiency of the YOLO algorithm under sufficient light conditions as well as the needs of object detection under poor light, this paper proposes...
The object described by more than one feature vector is called as a matrix-object. There is no outlier detection algorithm for matrix-object data at this stage. If we use the existing algorithms, the data needs to be preprocessed in advance. In order to better find outliers in a matrix-...
Earlier this year in March, we showed retinanet-examples, an open source example of how to accelerate the training and deployment of an object detection pipeline for GPUs. We presented the project at NVIDIA’s GPU Technology Conference in San Jose. This post discusses the motivation for this ...
The Occam platform is an AI algorithm platform that integrates six cutting-edge machine learning technologies: automatic pipeline, auto augmentation, distributed training acceleration, automatic model compression, auto-tuning, neural architecture search. With its comprehensive library of ...
Detection of social mental disorder using convolution neural network 2.1An algorithm assessing the mental health of college students This recognition system evaluates a variety of characteristics, including the student's grade point averages, the amount of material they consume, the degree of internet ...