A number of factors provide constraints on feature representations including context (such as prior knowledge), perceptual mechanisms (including feature detectors), and the category of the entity. Importantly, feature representations must also capture relations between features (e.g., spatial and ...
They comprise a set of learnable kernels, feature detectors, or filters with a small receptive field. These layers are responsible for generating feature maps from the input data through basic convolution operations. Let I be an input image. For all available local patches i in I, the ...
Answer to: There are various feature detectors in the brain corresponding to the various senses. Indicate whether the statement is true or false...
Optimizing the trade-off between single-stage and two-stage deep object detectors using image difficulty prediction. In 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), pp. 209–214 (IEEE, 2018). Jiménez-Sánchez, A., Kazi, A., Albarqouni...
Cognitive Psychology, 1973, 4, 130-155. GRAHAM, N. Spatial frequency channels in human vision: Detect- ing edges without edge detectors. In C. S. Harris (Ed.), Visual coding and adaptability. Hillsdale, N.1: Erlbaum, 1976. KINCH LA, R. A. The role of structural redundancy in the ...
In this part, we report the superiority of our method when it is used in another domain of computer vision. Visual saliency has been a fundamental problem in neuroscience, psychology, neural systems, and computer vision for a long time. In computer vision, detecting and segmenting salient object...
In the canonical formulation of Quick (1974), a strength of 2−1/k threshold units is necessary for two equally detectable single stimulus components if detection is by two independent families of detectors (Meinhardt, 1999, Meinhardt, 2000, Meinhardt and Persike, 2003, Watson, 1982). Here,...
Although these detectors often give very good performance and real-time detection, they do not attempt to mimic the HVS and require a training phase for model learning. In general, (convolutional) neural networks deeply rely on the optimization of their weights, as well as on the presence of ...
Our hypothesis was that face-selective regions in human ventral cortex might be organized into faciotopic maps, in which face feature detectors form a map whose topology matches that of a face. Faces, and especially the eye region, are frequently fixated from an early age (Farroni et al., ...
They comprise a set of learnable kernels, feature detectors, or filters with a small receptive field. These layers are responsible for generating feature maps from the input data through basic convolution operations. Let I be an input image. For all available local patches i in I, the ...