Biologically plausible saliency networks for object recognition
نویسندگان
چکیده
منابع مشابه
Biologically plausible saliency mechanisms improve feedforward object recognition
The biological plausibility of statistical inference and learning, tuned to the statistics of natural images, is investigated. It is shown that a rich family of statistical decision rules, confidence measures, and risk estimates, can be implemented with the computations attributed to the standard neurophysiological model of V1. In particular, different statistical quantities can be computed thr...
متن کاملA biologically plausible computational model for auditory object recognition.
Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spi...
متن کاملUnsupervised Learning of Biologically Plausible Object Recognition Strategies
Recent psychological and neurological evidence suggests that biological object recognition is a process of matching sensed images to stored iconic memories. This paper presents a partial implementation of (our interpretation of) Kosslyn's biological vision model, with a control system added to it. We then show how reinforcement learning can be used to control and optimize recognition in an unsu...
متن کاملToward a More Biologically Plausible Model of Object Recognition
Rapidly and reliably recognizing an object (is that a cat or a tiger?) is obviously an important skill for survival. However, it is a difficult computational problem, because the same object may appear differently under various conditions, while different objects may share similar features. A robust recognition system must have a capacity to distinguish between similar-looking objects, while be...
متن کاملComplex Object Recognition Using a Biologically Plausible Neural Model
The complex object recognition tasks are still one big problem in neurocomputing today. This paper presents a method of detecting and recognizing complex objects, in cluttered environment, in a purely feed-forward way, being able to account for ultra-rapid visual categorization. We used a retinotopic architecture of simple spiking neurons with different types of receptive fields, organized in a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Systems Neuroscience
سال: 2009
ISSN: 1662-5137
DOI: 10.3389/conf.neuro.06.2009.03.099