We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14). The main hallmark of this architecture is the improved utilization of the computing resources inside the network. By a carefully crafted design, we increased the depth and width of the network while keeping the computational budget constant. To optimize quality, the architectural decisions were based on the Hebbian principle and the intuition of multi-scale processing. One particular incarnation used in our submission for ILSVRC14 is called GoogLeNet, a 22 layers deep network, the quality of which is assessed in the context of classification and detection.

/pdf/going-deeper-with-convolutions-1yobw2o2ds.pdf

Going deeper with convolutions

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

http://www.cnbc.pt/jpmatos/29.%20Bradley.pdf?origin=publicationDetail

Measuring emotion: The self-assessment manikin and the semantic differential

Well-being : the foundations of hedonic psychology

Emotional Memory: A Dimensional Analysis

https://csea.phhp.ufl.edu/Publications/276.%20McTeague_FearfulImagerySocPhobia_2009.pdf

Fearful imagery in social phobia: generalization, comorbidity, and physiological reactivity.

State anxiety and affective physiology: effects of sustained exposure to affective pictures.

Studies of the long-term recency effect: Support for a contextually guided retrieval hypothesis.

Our view is that fundamental appetitive and defensive motivation systems evolved to mediate a complex array of adaptive behaviors that support the organism’s drive to survive—defending against threat and securing resources. Activation of these motive systems engages processes that facilitate attention allocation, information intake, sympathetic arousal, and, depending on context, will prompt tactical actions that can be directed either toward or away from the strategic goal, whether defensively or appetitively determined. Research from our laboratory that measures autonomic, central, and somatic reactions when processing emotional scenes is described which indicates that motivationally relevant cues, whether appetitive or defensive, capture attention preferentially, prompt enhanced perceptual processing and information gathering, and occasion metabolic arousal that mobilizes the organism for coping actions.

/pdf/appetitive-and-defensive-motivation-goal-directed-or-goal-2wypeg6nc8.pdf

Margaret M. Bradley

Papers

Emotional Memory: A Dimensional Analysis

Fearful imagery in social phobia: generalization, comorbidity, and physiological reactivity.

State anxiety and affective physiology: effects of sustained exposure to affective pictures.

Studies of the long-term recency effect: Support for a contextually guided retrieval hypothesis.

Appetitive and Defensive Motivation: Goal-Directed or Goal-Determined?