We propose a (neat) real-time face del.ect.or using a cascade of parallel neuTal net.work: (NN) ensembles for enhanced detection aCCUTacy and efficiency. First, we fon7/. a coordinated NN ensemble by sequentially tmining a set of neuml netw01ks with the same topology. The I.mining implicitly paTtitions the face space into a nurnbeT of di.~joint n:gions, and each NN 'is specialized in a spec~fic S11,b-l·egion. Second, to reduce the /.otal comp'lttal.ion cost for t.he face det.ect.ion, a series of NN ensembles aTe cascaded s1tch thai. the complexity of base nel:w01'ks increases. Our pTOJlosed apJlTOach achieves 1/,P to 94 % detection Tate (CM U + MIT test set) and 3-4 % frames/sec. det.ect.ion speed on a nan7/.al PC (P-IV, 3.0GHz)
Computerized human face processing (detection, recognition, synthesis) has known an intense research...
Face detection is an important problem in computer vision research and applications are getting tren...
Enthusiasm for neural computing seems, at present, to know no bounds. Neural networks are powerful ...
We propose a (neat) real-time face del.ect.or using a cascade of parallel neuTal net.work: (NN) ense...
We propose a fast face detector using an efficient architecture based on a hierarchical cascade of n...
A neural network based face detection system is pre-sented. Statistical pattern recognition (PR) tec...
Abstract:- In this paper, a real time face detection method using several small size neural networks...
We present a neural network-based face detection system. A retinally connected neural network examin...
Abstract- In this paper, a new approach to reduce the computation time taken by neural networks for ...
Multi‐task cascaded convolutional neural network (MTCNN) is a human face detection architecture whic...
Face detection for security cameras monitoring large and crowded areas is very important for public ...
We present a neural network-based face detection system. A retinally connected neural network examin...
Abstract. In this paper, we consider the problem of face detection un-der pose variations. Unlike ot...
We present a neural network-based face detection system. A retinally connected neural network examin...
We present a neural network-based face detection system. A retinally connected neural network examin...
Computerized human face processing (detection, recognition, synthesis) has known an intense research...
Face detection is an important problem in computer vision research and applications are getting tren...
Enthusiasm for neural computing seems, at present, to know no bounds. Neural networks are powerful ...
We propose a (neat) real-time face del.ect.or using a cascade of parallel neuTal net.work: (NN) ense...
We propose a fast face detector using an efficient architecture based on a hierarchical cascade of n...
A neural network based face detection system is pre-sented. Statistical pattern recognition (PR) tec...
Abstract:- In this paper, a real time face detection method using several small size neural networks...
We present a neural network-based face detection system. A retinally connected neural network examin...
Abstract- In this paper, a new approach to reduce the computation time taken by neural networks for ...
Multi‐task cascaded convolutional neural network (MTCNN) is a human face detection architecture whic...
Face detection for security cameras monitoring large and crowded areas is very important for public ...
We present a neural network-based face detection system. A retinally connected neural network examin...
Abstract. In this paper, we consider the problem of face detection un-der pose variations. Unlike ot...
We present a neural network-based face detection system. A retinally connected neural network examin...
We present a neural network-based face detection system. A retinally connected neural network examin...
Computerized human face processing (detection, recognition, synthesis) has known an intense research...
Face detection is an important problem in computer vision research and applications are getting tren...
Enthusiasm for neural computing seems, at present, to know no bounds. Neural networks are powerful ...