IL2M: Class Incremental Learning With Dual Memory 2019 ICCV End-to-end incremental learning 2018 ECCV Semi-supervised CL [Back to top] Semi-supervised CL is an extension of traditional CL that allows each task to incorporate unlabeled data as well. Paper TitleYearConference/Journal Continual Learn...
YOLO architectures are good at real-time processing and can be trained end to end in order to improve accuracy. Nevertheless, YOLO struggles to generalize groups of small objects [157–159]. YOLOv2 was used in [160] to recognize oil industry facilities. 5.7 Discussion Table 10 summarizes the...
which is also a function. The final layer of network operates on the outputs from the previous layers, which are also functions. So in effect, the entire model from the input layer right through to the loss calculation is just one big...
We report a complete deep-learning framework using a single-step object detection model in order to quickly and accurately detect and classify the types of manufacturing defects present on Printed Circuit Board (PCBs). We describe the complete model arch
In order to optimize the features, they applied harris hawk's optimization technique. For performance evaluation, the efficacy of the suggested model was compared with current machine learning techniques. Classifier performance was evaluated using the UCI machine repository. Mary Dayana and Sam Emmanuel...
As complexity and capabilities of Artificial Intelligence technologies increase, so does its potential for misuse. Deepfake videos are an example. They are
The accuracy metric is used due to the generally balanced class distribution of the datasets, as shown in Table 1. The CNN model is used for feature extraction as a benchmark classifier to evaluate the power of the hybrid learner. Also, two different hybrid approaches are used as benchmark ...
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VoTT 2.6k Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos. espnet 2.6k End-to-End Speech Processing Toolkit ltp 2.6k Language Technology Platform Learn_Deep_Learning_in_6_Weeks 2.6k This is the Curriculum for "Learn Deep Lear...
Classifier 1 is trained to recognise bifurcation trajectories based on middle portions of the time series, whereas Classifier 2 is trained on end portions (see Methods). In this way, Classifier 1 provides an earlier signal of a bifurcation and Classifier 2 provides a more specific signal, as ...