Ovum est in multis reptilibus cellula ovum a masculo fecundata, quam scientiati zygotum (ex verbo Graeco ζυγωτόν) appellant. Ovum est ergo eodem tempore forma et momentum progressionis vitae novi animantis.
Ovum animale, omnino galli, in hominibus solitaneus cibus est. Dicere licet se confectum esse a tribus partibus, quarum una cortex, qui id tegit, deinde vitellus, id est circus pulpae flavae adipum et proteinorum qui in eo situs est, et albumen, liquor translucidus qui eum circumdat.
Index
1Bibliographia
2Nexus interni
3Nexus externus
4Pinacotheca
Bibliographia |
Hanneke Meijer, "Duck egg blue and oviraptor green: study reconstructs colour of dinosaur eggs" on The Guardian: Science (11 Octobris 2017)
J. Wiemann et al., "Dinosaur origin of egg color: oviraptors laid blue-green eggs" in PeerJ no. 3706 (29 Augusti 2017) 5:e37062017
Nexus interni
Doctor Eggman
Ovum Colombinum
Nexus externus |
Vicimedia Communia plura habent quae ad ova spectant.
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...
