Titlebook: Handwriting Recognition; Soft Computing and P Zhi-Qiang Liu,Jinhai Cai,Richard Buse Book 2003 Springer-Verlag Berlin Heidelberg 2003 Markov

malignant

書(shū)目名稱Handwriting Recognition影響因子(影響力)




書(shū)目名稱Handwriting Recognition影響因子(影響力)學(xué)科排名




書(shū)目名稱Handwriting Recognition網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Handwriting Recognition網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Handwriting Recognition被引頻次




書(shū)目名稱Handwriting Recognition被引頻次學(xué)科排名




書(shū)目名稱Handwriting Recognition年度引用




書(shū)目名稱Handwriting Recognition年度引用學(xué)科排名




書(shū)目名稱Handwriting Recognition讀者反饋




書(shū)目名稱Handwriting Recognition讀者反饋學(xué)科排名

GRIN

意外的成功

apropos

Zhi-Qiang Liu,Jinhai Cai,Richard Buseagnetic field (~1.10?kA/m and 200?kHz), and the heat generated by them was assessed by an infrared camera. The resulting thermal images were processed in MATLAB after the thermographic calibration of the infrared camera. The results show the potential to use this thermal technique for the improvement and advance of MFH as a clinical therapy.

大都市

Zhi-Qiang Liu,Jinhai Cai,Richard Buseing;virtual reality; observing humans; spectral imaging and processing; intelligenttransportation systems; visual perception and robotic systems. Part II (LNCS9475): applications; 3D computer vision; computer graphics; segmentation;biometrics; pattern recognition; recognition; and virtual reality..

無(wú)底

Markov Models with Spectral Features for Handwritten Numeral Recognition,introduces Fourier descriptors for spectral features. Section 4.3 presents the Markov model-based method for recognizing handwritten numerals. This chapter also presents efficient re-estimation and evaluation algorithms. The results of handwritten numeral recognition using the proposed method are given in Section 4.4.

下級(jí)

Markov Random Field Models for Recognizing Handwritten Words,ng measurements. The relaxation labeling algorithm is used to maximize the global compatibilities of the MRF models. We investigate the influence of neighborhood size and iteration number of relaxation labeling on recognition rates.

相容

責(zé)問(wèn)

1434-9922 handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the pr

貞潔

que is developed to address these new challenges by means of an advancing front guided by a sphere packing methodology. The method is fairly simple and can efficiently triangulate point clouds into high quality meshes. The substantiated experimental results demonstrate the robustness and the generality of the proposed method.