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A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition, and won the ImageNet Large Scale Visual Recognition Challenge of that year. [2] [3]
Emotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context.
Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) 7,356 video and audio recordings of 24 professional actors. 8 emotions each at two intensities. Files labelled with expression. Perceptual validation ratings provided by 319 raters. 7,356 Video, sound files Classification, face recognition, voice recognition 2018 [89] [90]
Electronic devices such as robots are increasingly able to mimic human emotion. Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. [1]
Artificial empathy or computational empathy is the development of AI systems—such as companion robots or virtual agents—that can detect emotions and respond to them in an empathic way. [ 1 ] Although such technology can be perceived as scary or threatening, [ 2 ] it could also have a significant advantage over humans for roles in which ...
Inception [1] is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed Inception v1).). The series was historically important as an early CNN that separates the stem (data ingest), body (data processing), and head (prediction), an architectural design that persists in all modern
[67] [68] In 1982 the Crossbar Adaptive Array gave a neural network model of cognition-emotion relation. [65] [69] It was an example of a debate where an AI system, a recurrent neural network, contributed to an issue in the same time addressed by cognitive psychology.
LeNet-5 architecture (overview). LeNet is a series of convolutional neural network structure proposed by LeCun et al. [1].The earliest version, LeNet-1, was trained in 1989.In general, when "LeNet" is referred to without a number, it refers to LeNet-5 (1998), the most well-known version.