Jujutsu
Multi tool use
Litterae Iaponicae quae
jujutsu sonant
listen
info
Jujutsu, vel litteris Iaponicis 柔術, aliter interdum Yawara, est ars[1] antiqua pugnandi sine armis,[1][2] quae Iaponiae inventa est. Ex ea Jigoro Kano iudonem condidit. Cum enim ars non iam recte usa esset, arbitratus est imperator Iaponiae tot elementa in schola unica conferre,[2][3] quot reperta essent, ex quibus artes recentiores, quibus hodie generaliter utantur, conceptae sunt.[1] Iuiutsu excultus est ut dimicet samurai ut modo vincat adversarium armati in qua non armam utitur aut breve armam.
Iuventus in disciplina, circa 1920
Bibliographia |
↑ 1.01.11.2 Takahashi, Masao (May 3, 2005). Mastering Judo. Human Kinetics. p. viii. ISBN 0-7360-5099-X
↑ 2.02.1 Mol, Serge (2001). Classical Fighting Arts of Japan: A Complete Guide to Koryū Jūjutsu. Tocii Iaponiae: Kodansha International. pp. 24–54. ISBN 4-7700-2619-6
↑ Kanō, Jigorō (2006) [2005]. "A Brief History of Jujutsu". In Murata, Naoki. Mind over muscle: writings from the founder of Judo. trans. Nancy H. Ross (2 ed.). Japan: Kodansha International. p. 13. ISBN 4-7700-3015-0
Nexus externus |
|
Vicimedia Communia plura habent quae ad Jujutsu spectant.
|
U,Fny8C 0lfOx09UVVNYy3QJFD2lX,OFbsFZYDnOIPWO3
Popular posts from this blog
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...
1
$begingroup$
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...
1
$begingroup$
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...
listen info
