Aegidius Deleuze (Francice: Gilles Deleuze [ʒil dəˈløːz] (natus Lutetiae die 18 Ianuarii 1925; ibidem mortuus die 4 Novembris 1995) fuit philosophus Francicus theoria structuralismo et postmodernismo.
Index
1Opera
2Nexus interni
3Bibliographia
4Nexus externi
Opera |
Verba quae insequuntur vicificanda sunt ut rationibus qualitatis et Latinitatis propositis obtemperent. Quaesumus emenda.
Sua opera, solo scripta:
"Philosophia critica Kantii" (Francice: La philosophie critique de Kant), 1963
"Nietzsche", 1965
"Preasentatio de Sacher-Masoch", (idem: Présentation de Sacher-Masoch), 1967
"Spinoza et problema expressionis" (Idem: Spinoza et la problème d'expression), 1968
"Differentia et repetitio" (Idem: Diffférence et répétition), 1968
Deinde cum Felix Guattari conscripta:
"Anti-Oedipus" (Francice: L'Anti-OEdipe, capitalisme et schizophrénie), Les éditions de minuit 1972, ISBN 2-7073-0067-5
"Kafka" (Idem: Kafka - pour une literature mineure, 1975
"Mille Plani" (Idem: Mille Plateau, capitalisme et schizophrénie), 1980
"Quod est philosophia?" (Idem: Qu'est-ce que la philosophie?), 1991
Nexus interni
Univocitas entis
Bibliographia |
Felix Guattari and Gilles Deleuze: a Bibliography, compilavit Joan Nordquist, Santa Cruz Californiae 1992, ISBN 0-937855-49-9
Studia
Balke, Friedrich, Gilles Deleuze. Francofurti ad Moenum 1998. ISBN 3593359804.
Fahle, Oliver, et Lorenz Engell, (eds.), Le cinéma selon Deleuze. Verlag der Bauhaus-Universität Weimar, Presses de la Sorbonne Nouvelle, Vimariae & Parisiis 1999, ISBN 3-86068-060-9
Nexus externi |
Lexici biographici: • Большая российская энциклопедия • Encyclopædia Britannica • Internet Encyclopedia of Philosophy
Vicimedia Communia plura habent quae ad Aegidium Deleuze spectant.
De Aegidio Deleuze apud Universitatem Staffordiensem pagina a Daniel Smith scripta
Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
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This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
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I have this LSTM model model = Sequential() model.add(Masking(mask_value=0, input_shape=(timesteps, features))) model.add(LSTM(100, dropout=0.2, recurrent_dropout=0.2, return_sequences=False)) model.add(Dense(features, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy']) and shapes X_train (21, 11, 5), y_train (21, 5) . Each timestep is represented by 5 features and return_sequences is set to False because I want to predict one 5D array (the next timestep) for each input sequence of 11 timesteps. I get the error ValueError: y_true and y_pred have different number of output (5!=1) If I reshape the data as X_train (21, 11, 5), y_train (21, 1, 5) instead I get the error ValueError: Inva...
