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t appealed against the disciplinary action your employer has taken against you. However, if you win your case, the tribunal may reduce any pensation awarded to you as a result of your failure to appeal. Remember that in most cases you must make an application to an employment tribunal within three months of the date when the event you are plaining about happened. If your application is received after this time limit, the tribunal will not usually accept it. If you are worried about how the time limits apply to you, take advice from one of the anisations listed under Further help. Employment tribunals are less formal than some other courts, but it is still a legal process and you will need to give evidence under an oath or affirmation. 44 Most people find making a claim to an employment tribunal challenging. If you are thinking about making a claim to an employment tribunal, you should get help straight away from one of the anisations listed under Further help. If you are being repr。 imshow(I) % % Executes during object creation, after setting all properties. function axes3_CreateF(hObject, eventdata, handles) % hObject handle to axes3 (see GCBO) % eventdata reserved to be defined in a future version of MATLAB % handles empty handles not created until after all CreateFs called % Hint: place code in OpeningF to populate axes3 %Programmed by Usman Qayyum g an employment tribunal claim Employment tribunals sort out disagreements between employers and employees. You may need to make a claim to an employment tribunal if: ? you don39。 axes() 43 imgpath=STRCAT(pathname,filename)。Test Image39。*.bmp39。)。,39。)) set(hObject,39。), get(0,39。 isequal(get(hObject,39。)) returns contents of box as a double 42 % % Executes during object creation, after setting all properties. function box_CreateF(hObject, eventdata, handles) % hObject handle to box (see GCBO) % eventdata reserved to be defined in a future version of MATLAB % handles empty handles not created until after all CreateFs called % Hint: edit controls usually have a white background on Windows. % See ISPC and COMPUTER. if ispc amp。) returns contents of box as text % str2double(get(hObject,39。) % function box_Callback(hObject, eventdata, handles) % hObject handle to box (see GCBO) % eventdata reserved to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Hints: get(hObject,39。 end display(39。Incorrectly Recognized39。\39。ORL\S39。 matches with the image of subject 39。Error== Testing Image of Subject 39。)。))) msgbox ( 39。,num2str(M),39。 if (subjectindex == M) axes () 41 %image no: 5 is shown for visualization purpose imshow(imread(STRCAT(39。 getString_end=getString_end(end)1。\39。 getString_start=getString_start(end)+1。S39。 M = ceil(M/5)。 K = K + 1。 end img_bin_hist_sum(K,1) = sum。 40 K = 1。 end end test_processed_bin(K) = sum/bin_num。 sum = 0。 test_processed_bin(K) = sum/bin_num。 K = 1。 39 end end end [r c] = size(test_hist_img)。 for i=1:1:rows for j=1:1:cols if( I(i,j) == 0 ) test_hist_img(max_hist_level) = test_hist_img(max_hist_level) + 1。 test_processed_bin(form_bin_num) = 0。train39。 global train_processed_bin。 train_processed_bin。) save 39。 end display (39。 else sum = sum + train_hist_img(j,i)。 K = K + 1。 for j=1:1:r if( (mod(j,bin_num)) == 0 ) sum = sum + train_hist_img(j,i)。 sum = 0。 end end end K = K + 1。 for i=1:1:rows for j=1:1:cols if( I(i,j) == 0 ) train_hist_img(max_hist_level, K) = train_hist_img(max_hist_level, K) + 1。) )。,int2str(X),39。,int2str(Z),39。 for Z=1:1:total_sub for X=1:2:sub_img %%%train on odd number of images of each subject I = imread( strcat(39。 K = 1。 global total_sub train_img sub_img max_hist_level bin_num form_bin_num。 % hObject handle to figure % eventdata reserved to be defined in a future version of MATLAB % handles structure with handles and user data (see GUIDATA) % Get default mand line output from handles structure varargout{1} = 。 form_bin_num = 29。 max_hist_level = 256。 train_img = 200。 global total_sub train_img sub_img max_hist_level bin_num form_bin_num。 % Update handles structure guidata(hObject, handles)。 else gui_mainf(gui_State, varargin{:})。 ischar(varargin{1}) = str2func(varargin{1})。 if nargin amp。gui_Callback39。gui_LayoutF39。gui_OutputF39。gui_OpeningF39。gui_Singleton39。gui_Name39。 [4] 何國(guó)輝,甘俊英 .PCALDA算法在性別鑒別中的應(yīng)用 [J].中國(guó)圖像圖形學(xué)報(bào),2021, 32( 19): 208211. [5] 王聃,賈云偉,林福嚴(yán) .人臉識(shí)別系統(tǒng)中的特征提取 [J].自動(dòng)化學(xué)報(bào), 2021,21( 73) . [6] 張儉鴿,王世卿,盛光磊 .基于小波和 DFBPCA 的人臉識(shí)別算法研究 [J].自動(dòng)化學(xué)報(bào), 2021, 23( 21) . [7] 曹林,王東峰,劉小軍,鄒謀炎 .基于二 維 Gabor 小波的人臉識(shí)別算法 [J].電子學(xué)報(bào), 2021, 28( 3) 490494 [8] 焦峰,山世光,崔國(guó)勤,高文,李錦濤 .基于局部特征分析的人臉識(shí)別方法 [J].自動(dòng)化學(xué)報(bào), 2021, 15( 1): 5358 [9] Wangmeng Zuo, Kuanquan Wang, David Zhang, Hongzhi Zhang. Combination of two novel LDAbased methods for face recognition[C].Proceedings of the IEEE, 2021: 735742 [10] 徐倩,鄧偉 .一種融合兩種主成分分析的人臉識(shí)別方法 [J].計(jì)算機(jī)學(xué)報(bào), 2021,43( 25): 195197 [11] 劉貴喜,楊萬(wàn)海 .基于小波分解的圖像融和方法及性能評(píng)價(jià) [J].自動(dòng)化學(xué)報(bào), 31 2021, 28( 6): 927934 [12] 周嬪,馬少平,蘇中 .多分類器合成方法綜獻(xiàn) [J].自動(dòng)化學(xué)報(bào), 2021, 28( 1):122124 [13] 王蘊(yùn)紅,范偉,譚鐵牛 .融合全局與局部特征的子空間人臉識(shí)別算法 [J].電子學(xué)報(bào), 2021, 28( 10): 16571662 [14] 莊哲民,張阿妞,李芬蘭 .基于優(yōu)化的 LDA算法人臉識(shí)別研究 [J].中國(guó)圖像圖形學(xué)報(bào), 2021, 29( 9)